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4th IEEE International Conference on Cloud Computing and Intelligence Systems (IEEE CCIS)

作者： Qiu, Lei Lou, Yuansheng Chang, Min Ho Hai Univ Coll Comp & Informat Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781509012565

In the theme crawler. the Shark-Search algorithm is insufficient to consider the global web page. In this paper, the pagerank algorithm is used to calculate the URL's authority to make up for this shortcoming, and Shark-pagerank algorithm, which adopts the anchor text, the context near the anchor text and authoritative value of web page to measure the value of the URL, is proposed in this paper. The experiment results show that the new algorithm improves the speed and accuracy of the query, and the algorithm has good stability and scalability.

关键词： Theme crawler Shark-Search algorithm pagerank algorithm Vertical

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Experts Ranking on the Enterprise Microblogging based on the pagerank algorithm

Experts Ranking on the Enterprise Microblogging based on the...

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7th IEEE Asia-Pacific Services Computing Conference (APSCC)

作者： Li, Ning Ning, Ke Zhang, LiangJie Wang, Yan Kingdee Res Shenzhen Peoples R China

ISBN: (纸本)9780769548975;9781467348256

With the rapid development of social networks services (SNS), Enterprise microblogging gradually shows its importance in business management. In the Enterprise Microblogging, If we can Accurately search and rank the experts, it can greatly enhance the operational rate of the Enterprise. In this article, Based on Google's pagerank algorithm, combined with the labels of the expert on enterprise microblogging network, we can rank the experts in the enterprise microblogging network according to the influence of the expert. Therefore, we can improve the precision rate of the expert searching results for the user.

关键词： Enterprise microblogging Expert ranking pagerank algorithm tag

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A Value Evaluation Method for Papers Based on Improved pagerank algorithm

A Value Evaluation Method for Papers Based on Improved PageR...

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2nd International Conference on Computer Science and Network Technology (ICCSNT)

作者： Qiao, Hongguang Wang, Yu Liang, Yanhua Hebei Univ Coll Math & Comp Sci Baoding Peoples R China

ISBN: (纸本)9781467329644;9781467329637

Because of the similarity of link network and citation network, bringing the pagerank algorithm to citation analysis to evaluate the value of a paper is a feasible method. But there are some problems in using the method directly. Therefore, combined with the characteristics of the citation network, this paper proposes an alternative method for evaluating the value of a paper based on improved pagerank algorithm. Taking into account some factors such as the impact factor of the journal where the paper is published and the correlation of two papers, the method computes the total value of a paper from two aspects, which are the paper's inherent value and the value passed from other papers. The experimental results show the feasibility and effectiveness of this method.

关键词： pagerank algorithm paper's value citation analysis impact factor correlation

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An Outlier Detection Method Based on pagerank algorithm 12

An Outlier Detection Method Based on PageRank Algorithm

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12th International Conference on Computational Intelligence and Security (CIS)

作者： Huang, Zhan Long, Shun Jiang, Yuying Chen, Qian Jinan Univ Dept Comp Sci Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781509048403

Outlier detection is an important research problem in data mining and image analysis. In this paper, the ideas in the pagerank algorithm are borrowed to construct a novel outlier detection method. In this method, three detecting stages are performed to detect three different types of outliers by using different detecting strategies. The whole process is called tri-stage detection. Effectiveness of the proposed method is verified by three simulation experiments carried out on the Matlab platform.

关键词： outlier detection pagerank algorithm data mining

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Subway network critical nodes detection based on improved pagerank algorithm 2

Subway network critical nodes detection based on improved pa...

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2nd International Conference on Robotics Systems and Vehicle Technology, RSVT 2020

作者： Li, Sasa Guan, Deyong Qin, Wei School of Transportation College Shandong University of Science and Technology Qingdao266590 China

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A Novel Feature-based pagerank algorithm for Node Importance Ranking 34

A Novel Feature-based PageRank Algorithm for Node Importance...

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34th Chinese Control and Decision Conference (CCDC)

作者： Xiao, Junyi Yi, Jingwen Chai, Li Wuhan Univ Sci & Technol Engn Res Ctr Met Automat & Measurement Technol Wuhan 430081 Peoples R China

ISBN: (纸本)9781665478960

Node importance ranking is one of key problems in the study of complex networks. The classical pagerank algorithm only focus on the network structure, which lead to inaccurate ranking result. By introducing the features of node attributes and user preference, a novel feature-based pagerank (FBPR) algorithm is proposed to identify the important nodes accurately and efficiently. The weight matrix and the fixed teleportation vector are redesigned by the feature similarities in the FBPR model. For different application scenarios, we can get different ranking results by adjusting the node attributes factor and the user preference factor. Finally, several simulation experiments are presented to verify the effectiveness of the FBPR algorithm.

关键词： pagerank algorithm feature similarity node attribute user preference

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Study on the influence of the cooperation network based on the pagerank algorithm

Study on the influence of the cooperation network based on t...

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International Conference on Electric, Electronic and Control Engineering, ICEECE 2015

作者： Chen, Bin Bin Wu, Hao Ran Xu, Gong Wen School of Mathematical Sciences Heilongjiang University Harbin China School of Computer Science and Technology Shandong Jianzhu University Jinan China

ISBN: (纸本)9781138028425

This article lay emphasis on complex co-author network problems and improved the traditional pagerank algorithm to build an author influence model and paper influence model, and Erdos’s co-author network were analyzed and discussed as an example. The results show that this model is effective, and can be extended to more social networks, breaking the limitations of the pagerank algorithm. © 2015 Taylor & Francis Group, London.

关键词： Co-author cooperation network pagerank algorithm The influence of paper

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Structural Vulnerability Assessment of Multi-energy System Using a pagerank algorithm

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Energy Procedia 2019年 158卷 6466-6471页

作者： Yichen Shen Chenghong Gu Pengfei Zhao University of Bath Claverton Down BA2 7JY Bath UK

Severe natural catastrophes may directly cause large-scale cascading failures in energy systems. This paper presents a comprehensive scheme of vulnerability assessment for multi-energy systems, including both electricity and natural gas. Differing from cascading failure theory, this scheme employs pagerank algorithm to measure the structural importance of the integrated system. A modified weighted pagerank methodology is applied to determine the importance of nodes in both natural gas and electricity networks. The effectiveness of this scheme is demonstrated and analyzed via an integrated energy system in the case study. This algorithm can help identify the weakness in the integrate energy system so that purposeful planning and operation strategies can be deployed to increase the security.

关键词： Vulnerability assessment Combined Gas-electric system pagerank algorithm

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A Bias-Free Time-Aware pagerank algorithm for Paper Ranking in Dynamic Citation Networks

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Intelligent Information Management 2022年第2期14卷 53-70页

作者： Moath Abu Dayeh Badie Sartawi Saeed Salah Department of Computer Science Al-Quds University Jerusalem Palestine

The process of ranking scientific publications in dynamic citation networks plays a crucial rule in a variety of applications. Despite the availability of a number of ranking algorithms, most of them use common popularity metrics such as the citation count, h-index, and Impact Factor (IF). These adopted metrics cause a problem of bias in favor of older publications that took enough time to collect as many citations as possible. This paper focuses on solving the problem of bias by proposing a new ranking algorithm based on the pagerank (PR) algorithm;it is one of the main page ranking algorithms being widely used. The developed algorithm considers a newly suggested metric called the Citation Average rate of Change (CAC). Time information such as publication date and the citation occurrence’s time are used along with citation data to calculate the new metric. The proposed ranking algorithm was tested on a dataset of scientific papers in the field of medical physics published in the Dimensions database from years 2005 to 2017. The experimental results have shown that the proposed ranking algorithm outperforms the pagerank algorithm in ranking scientific publications where 26 papers instead of only 14 were ranked among the top 100 papers of this dataset. In addition, there were no radical changes or unreasonable jump in the ranking process, i.e., the correlation rate between the results of the proposed ranking method and the original pagerank algorithm was 92% based on the Spearman correlation coefficient.

关键词： Bibliometric Citation Analysis pagerank algorithm Scientific Publications Metrics Time-Aware

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Identification of Key Lines for Multi-Photovoltaic Power System Based on Improved pagerank algorithm

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FRONTIERS IN ENERGY RESEARCH 2020年 8卷

作者： Feng, Hao Li, Sheng Li, Huaisen Nanjing Inst Technol Sch Elect Power Engn Nanjing Peoples R China CGN New Energy Investment Shenzhen Co LTD Nanjing Peoples R China

In order to accurately identify the key lines in the photovoltaic (PV) grid-connected system, an identification method based on the improved pagerank algorithm is proposed. Firstly, the correlation matrix reflecting the electrical characteristics of the system is constructed using the line current-carrying rate, line breaking power flow transfer rate and line coupling rate, to replace the original network topology matrix. Secondly, through the entropy method, a comprehensive evaluation index based on electrical betweenness, load deviation rate and voltage shock rate is constructed to improve the distribution of the initial pagerank (PR) value of the PV grid-connected system. To study the changes' impact of PVs active power outputs on the identification results of key lines in the Multi-PV power system, the HGWO-SVM (Hybrid Grey Wolves Optimized Support Vector Machine) algorithm was used to obtain the PVs daily outputs prediction curves and obtain fixed outputs of PVs at different periods, so as to study the impact of the variation of PV daily output on the key line identification. Taking the IEEE 39-node system containing multi-PV as an example, the identification results show that the improved pagerank algorithm is superior to the original method in line identification accuracy. The HGWO-SVM algorithm by adaptively modifying the cross operator and mutation operator also has a certain improvement in prediction accuracy. The changes of PVs daily outputs have different degree of influence on the line criticality (namely final PR value) during periods of high light intensity and other periods of light intensity.

关键词： line identification pagerank algorithm photovoltaic hybrid grey wolves optimized support vector machine multi-photovoltaic power system

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